sbart: Sequential BART for Imputation of Missing Covariates

Implements the sequential BART (Bayesian Additive
Regression Trees) approach to impute the missing covariates. The
algorithm applies a Bayesian nonparametric approach on factored
sets of sequential conditionals of the joint distribution of the
covariates and the missingness and applying the Bayesian additive
regression trees to model each of these univariate
conditionals. Each conditional distribution is then sampled using
MCMC algorithm. The published journal can be found at
<https://doi.org/10.1093/biostatistics/kxw009> Package provides a
function, seqBART(), which computes and returns the imputed
values.